A New Multiangle Method for Estimating Fractional Biocrust Coverage From Sentinel-2 Data in Arid Areas

Abstract

The spatio-temporal distribution of biocrusts can be used to monitor regional water resources in desert ecosystems. However, a lack of biocrust products from remotely sensed images with fine spatial resolution (FSR) limits scientific research in this area. To address this issue, we establish an estimation model for biocrusts (EMBC) in three steps for FSR images and map the large-scale fractional biocrust coverage ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FBC</i> ) in deserts using Sentinel-2 images with a spatial resolution of 10 m. Firstly, we develop a fraction biocrust cover index ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FBCI</i> ) based on radiative transfer theory. Next, a multi-angle calculation equation involving <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FBCI</i> is established and the parameters for a pixel dichotomy model are solved by an inverse method using a linear kernel-driven model. Finally, this pixel dichotomy model with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FBCI</i> is used to calculate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FBC</i> . We validate the model using field measurements and compare the validation results with those estimated by a random forest model and a backpropagation neural network model. This comparison demonstrates that the value of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FBC</i> estimated by EMBC is highly consistent with field measurements (root mean square error (RMSE) = 0.0774, systematic deviation = -4.05%). Furthermore, the values of FBC estimated with EMBC and the two other models show a high level of consistency in terms of spatial distribution (RMSE < 0.0998). We conclude that our EMBC can accurately estimate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FBC</i> in a desert and is an important technique for monitoring drought in an arid environment.